DBMS > AllegroGraph vs. Amazon Redshift vs. MonetDB vs. RavenDB

System Properties Comparison AllegroGraph vs. Amazon Redshift vs. MonetDB vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Large scale data warehouse service for use with business intelligence tools

A relational database management system that stores data in columns

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

allegrograph.com

aws.amazon.com/redshift

www.monetdb.org

ravendb.net

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.aws.amazon.com/redshift

www.monetdb.org/Documentation

ravendb.net/docs

Developer

Franz Inc.

Amazon (based on PostgreSQL)

MonetDB BV

Hibernating Rhinos

Initial release

2004

2012

2004

2010

Current release

8.0, December 2023

Dec2023 (11.49), December 2023

5.4, July 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

Mozilla Public License 2.0

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

RDF schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

bulk load of XML files possible

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SPARQL is used as query language

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

in Python

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Source-replica replication available in experimental status

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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